Jiang Guoqian, Kiefer Richard C, Sharma Deepak K, Prud'hommeaux Eric, Solbrig Harold R
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
W3C/MIT, Boston, MA, USA.
Stud Health Technol Inform. 2017;245:887-891.
A variety of data models have been developed to provide a standardized data interface that supports organizing clinical research data into a standard structure for building the integrated data repositories. HL7 Fast Healthcare Interoperability Resources (FHIR) is emerging as a next generation standards framework for facilitating health care and electronic health records-based data exchange. The objective of the study was to design and assess a consensus-based approach for harmonizing the OHDSI CDM with HL7 FHIR. We leverage a FHIR W5 (Who, What, When, Where, and Why) Classification System for designing the harmonization approaches and assess their utility in achieving the consensus among curators using a standard inter-rater agreement measure. Moderate agreement was achieved for the model-level harmonization (kappa = 0.50) whereas only fair agreement was achieved for the property-level harmonization (kappa = 0.21). FHIR W5 is a useful tool in designing the harmonization approaches between data models and FHIR, and facilitating the consensus achievement.
已经开发了多种数据模型,以提供标准化的数据接口,支持将临床研究数据组织成标准结构,用于构建集成数据存储库。HL7快速医疗保健互操作性资源(FHIR)正在成为促进基于医疗保健和电子健康记录的数据交换的下一代标准框架。本研究的目的是设计并评估一种基于共识的方法,用于使OHDSI公共数据模型(CDM)与HL7 FHIR协调一致。我们利用FHIR的W5(谁、什么、何时、何地以及为何)分类系统来设计协调方法,并使用标准的评分者间一致性测量方法评估它们在实现策展人之间共识方面的效用。在模型级协调方面达成了中度一致性(kappa = 0.50),而在属性级协调方面仅达成了一般一致性(kappa = 0.21)。FHIR W5是设计数据模型与FHIR之间协调方法以及促进达成共识的有用工具。